Intelligent control method and device for shock absorber assembly production

Abstract

The present invention discloses an intelligent control method and device for shock absorber assembly production, and relates to the field of intelligent control technology. The method comprises: receiving a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber components; performing variable constraint modulation on the H shock absorber components, and establishing a shock absorber assembly control variable constraint matrix; performing component assembly control decision on the H shock absorber components, and obtaining a shock absorber assembly control decision population; constructing a shock absorber assembly control fitness function and an assembly control decision reproduction constraint function; performing decision seed reproduction search and optimization on the shock absorber assembly control decision population, and obtaining a shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraint; and performing assembly control on the H shock absorber components according to the shock absorber assembly control optimization result. The method solves the technical problem of low assembly efficiency in the shock absorber assembly production process in the prior art, and achieves the technical effect of improving assembly efficiency.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control technology, and in particular to an intelligent control method and device for shock absorber assembly production. Background Art

[0002] With the rapid development of the automobile industry and the continuous improvement of consumers' requirements for automobile performance, the field of automobile parts manufacturing is facing unprecedented challenges and opportunities. As a key component in the automobile suspension system, the performance of the shock absorber plays a vital role in improving driving comfort and driving safety. However, the traditional shock absorber assembly production method generally has problems such as low production efficiency, difficult to ensure assembly accuracy, and unstable quality control, which has become a bottleneck restricting the further development of the shock absorber manufacturing industry. Therefore, in order to meet the market demand for high-quality shock absorbers and improve the automation and intelligence level of shock absorber assembly production, an intelligent control method and device for shock absorber assembly production are proposed, and then the problem of low assembly control efficiency in the shock absorber assembly production process is solved through intelligent means. Summary of the invention

[0003] The embodiments of the present application provide an intelligent control method and device for shock absorber assembly production, which solves the technical problem of low assembly efficiency in the shock absorber assembly production process in the prior art.

[0004] In view of the above problems, the embodiments of the present application provide an intelligent control method and device for shock absorber assembly production.

[0005] A first aspect of an embodiment of the present application provides an intelligent control method for shock absorber assembly production, the method comprising:

[0006] Receive a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber components, wherein H is a positive integer greater than 1; perform variable constraint modulation on the H shock absorber components according to the assembly control variable optimization breadth constraint, and establish a shock absorber assembly control variable constraint matrix; perform component assembly control decisions on the H shock absorber components according to the shock absorber assembly control variable constraint matrix, and obtain a shock absorber assembly control decision population; construct a shock absorber assembly control fitness function and an assembly control decision reproduction constraint function; perform decision seed reproduction search and optimization on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function, and the assembly control decision reproduction constraint function, and obtain a shock absorber assembly control optimization result that satisfies the reproduction search optimization constraint; perform assembly control on the H shock absorber components according to the shock absorber assembly control optimization result.

[0007] A second aspect of the embodiments of the present application provides an intelligent control device for shock absorber assembly production, the device comprising:

[0008] A receiving module, the receiving module is used to receive a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber components, wherein H is a positive integer greater than 1; a variable constraint modulation module, the variable constraint modulation module is used to perform variable constraint modulation on the H shock absorber components according to the assembly control variable optimization breadth constraint, and establish a shock absorber assembly control variable constraint matrix; an assembly control decision module, the assembly control decision module is used to perform component assembly control decision on the H shock absorber components according to the shock absorber assembly control variable constraint matrix, and obtain a shock absorber assembly control decision population; A function construction module, the function construction module is used to construct a shock absorber assembly control fitness function and an assembly control decision propagation constraint function; an optimization module, the optimization module is used to perform decision seed propagation search and optimization on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision propagation constraint function, and obtain a shock absorber assembly control optimization result that satisfies the propagation search optimization constraint; an assembly control module, the assembly control module is used to perform assembly control on the H shock absorber components according to the shock absorber assembly control optimization result.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, a shock absorber assembly production task is received, wherein the shock absorber assembly production task includes H shock absorber components, wherein H is a positive integer greater than 1. Then, variable constraint modulation is performed on the H shock absorber components according to the assembly control variable optimization breadth constraint, and a shock absorber assembly control variable constraint matrix is ​​established. Then, component assembly control decisions are made on the H shock absorber components according to the shock absorber assembly control variable constraint matrix, and a shock absorber assembly control decision population is obtained. Next, a shock absorber assembly control fitness function and an assembly control decision reproduction constraint function are constructed. Further, a decision seed reproduction search is performed on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, and a shock absorber assembly control optimization result that satisfies the reproduction search optimization constraint is obtained. Finally, assembly control is performed on the H shock absorber components according to the shock absorber assembly control optimization result. The technical problem of low assembly efficiency in the shock absorber assembly production process in the prior art is solved, and the technical effect of improving assembly efficiency is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0012] Figure 1 A schematic flow chart of an intelligent control method for shock absorber assembly production provided in an embodiment of the present application;

[0013] Figure 2 A schematic diagram of the structure of an intelligent control device for shock absorber assembly production provided in an embodiment of the present application.

[0014] Explanation of the reference numerals: receiving module 11 , variable constraint modulation module 12 , assembly control decision module 13 , function construction module 14 , optimization module 15 , assembly control module 16 . DETAILED DESCRIPTION

[0015] The embodiments of the present application solve the technical problem of low assembly efficiency in the shock absorber assembly production process in the prior art by providing an intelligent control method and device for shock absorber assembly production.

[0016] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0017] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or are inherent to these processes, methods, products or devices.

[0018] Embodiment 1

[0019] like Figure 1 As shown, the embodiment of the present application provides an intelligent control method for shock absorber assembly production, wherein the method includes:

[0020] A shock absorber assembly production task is received, wherein the shock absorber assembly production task includes H shock absorber assemblies, wherein H is a positive integer greater than 1.

[0021] The shock absorber assembly production task includes H shock absorber components, where H is a positive integer greater than 1, representing the specific number of shock absorber components that need to be processed in the shock absorber assembly production task. By receiving the shock absorber assembly production task, the assembly control can be optimized to ensure that each component can be assembled according to the predetermined standards and requirements, thereby improving production efficiency and product quality.

[0022] The H shock absorber components are subjected to variable constraint modulation according to the assembly control variable optimization breadth constraint, and a shock absorber assembly control variable constraint matrix is ​​established.

[0023] The assembly control variable optimization breadth constraint refers to a series of constraints that need to be considered when optimizing the assembly control variables in order to ensure the assembly quality and efficiency during the assembly process of the shock absorber assembly, including variable range constraints, process requirement constraints, etc. Variable range constraints mean that each assembly control variable has a reasonable value range, such as the size of the assembly force, the speed of the assembly, etc. These assembly control variables can be determined according to the material, structure and assembly requirements of the shock absorber assembly to ensure that the assembly process is carried out within a safe range. For example, the assembly force needs to vary within a certain Newton (N) range, and the assembly speed needs to be maintained within a specific millimeter / second (mm / s) range. Process requirement constraints refer to the restrictions set on the assembly control variables according to the assembly process and technical requirements of the shock absorber assembly, including requirements on assembly sequence, assembly accuracy, assembly clearance, etc., to ensure that the assembled shock absorber assembly meets the design requirements and performance. According to the assembly control variable optimization breadth constraint, the variable constraints of H shock absorber assemblies are modulated, including determining the value range of the variables, boundary conditions, constraint functions, etc. For example, a certain assembly force needs to vary within a certain range to ensure the tightness and safety of the assembly. The modulated control variables and their constraints are organized into a matrix form, namely, the shock absorber assembly control variable constraint matrix. The shock absorber assembly control variable constraint matrix will serve as the basis for assembly control decision-making to ensure that the decision-making process is carried out within the constraints.

[0024] Furthermore, the H shock absorber components are subjected to variable constraint modulation according to the assembly control variable optimization breadth constraint, and a shock absorber assembly control variable constraint matrix is ​​established, including:

[0025] According to the H shock absorber components, assembly control variables are retrieved to obtain a first shock absorber component assembly control variable set; according to the first shock absorber component assembly control variable set, coupling reduction optimization is performed to obtain a second shock absorber component assembly control variable set; according to the second shock absorber component assembly control variable set, assembly control value evaluation is performed to obtain a variable assembly control value evaluation distribution; according to the variable assembly control value evaluation distribution, the second shock absorber component assembly control variable set is arranged in descending order to obtain a third shock absorber component assembly control variable set; according to the assembly control variable optimization breadth constraint, the third shock absorber component assembly control variable set is optimized and screened to obtain a fourth shock absorber component assembly control variable set, wherein the assembly control variable optimization breadth constraint includes a component assembly control variable optimization dimension threshold; based on the fourth shock absorber component assembly control variable set, variable constraint information of the H shock absorber components is collected to generate the shock absorber assembly control variable constraint matrix.

[0026] Preferably, assembly control variables of H shock absorber assemblies are retrieved to obtain all control variables that need to be considered in the assembly process of each shock absorber assembly, such as assembly force, assembly angle, assembly speed, etc., to further form a first shock absorber assembly control variable set, which includes the assembly control variables of each shock absorber assembly; since some control variables may be coupled during the assembly process, that is, their changes will affect each other, the first shock absorber assembly control variable set is decoupled and optimized so that each control variable can change more independently, thereby making it easier to find the optimal assembly control scheme, and after decoupling optimization, the second shock absorber assembly control variable set is obtained; the second shock absorber assembly control variable set is evaluated for assembly control value, and a value score can be assigned to each control variable based on the expert team's evaluation of the degree of influence of each control variable on assembly quality, efficiency, etc., to form a variable assembly control variable set. The control value evaluation distribution of the variable assembly control value evaluation is obtained; according to the variable assembly control value evaluation distribution, the second shock absorber component assembly control variable set is arranged in descending order, that is, the control variables with higher value scores are arranged in front, and the control variables with lower value scores are arranged in the back, and after descending order, the third shock absorber component assembly control variable set is obtained; the assembly control variable optimization breadth constraint includes the component assembly control variable optimization dimension threshold, and the third shock absorber component assembly control variable set is optimized and screened according to the assembly control variable optimization breadth constraint, so as to reduce the number of control variables while maintaining a certain optimization breadth, so as to make the assembly control process more concise and efficient, and then obtain the fourth shock absorber component assembly control variable set; based on the fourth shock absorber component assembly control variable set, variable constraint information is collected for H shock absorber components, including collecting the assembly control variables and their constraints of each component, and organizing them into a matrix form, that is, the shock absorber assembly control variable constraint matrix.

[0027] Further, performing decoupling optimization according to the first shock absorber assembly control variable set to obtain a second shock absorber assembly control variable set includes:

[0028] According to the first shock absorber assembly control variable set, pairwise coupling evaluation is performed to obtain an assembly control variable coupling evaluation set; an assembly control variable coupling evaluation threshold is obtained; according to the assembly control variable coupling evaluation threshold and the assembly control variable coupling evaluation set, the first shock absorber assembly control variable set is subjected to coupling reduction optimization to obtain the second shock absorber assembly control variable set whose arbitrary assembly control variable coupling evaluation coefficient is less than the assembly control variable coupling evaluation threshold.

[0029] Preferably, pairwise coupling evaluation is performed on the first shock absorber component assembly control variable set, that is, the coupling degree between the pairwise assembly control variables is determined, and the coupling evaluation index between the pairwise assembly control variables can be calculated by an expert team, and the coupling evaluation between all pairwise variables is organized into a set, that is, the assembly control variable coupling evaluation set, and the assembly control variable coupling evaluation set includes the coupling evaluation between all variable pairs in the assembly control variable set; according to the assembly requirements and quality standards, an assembly control variable coupling evaluation threshold is determined in combination with expert opinions to ensure that the coupling degree in the assembly process is within an acceptable range; according to the assembly control variable coupling evaluation set and the coupling evaluation threshold, the assembly control variable set is subjected to coupling reduction optimization, and the values ​​of the assembly control variables are adjusted to find a new assembly control variable set so that the coupling evaluation coefficients of any two variables therein are less than the coupling evaluation threshold. After coupling reduction optimization, a new assembly control variable set, that is, the second shock absorber component assembly control variable set, is obtained, and the second shock absorber component assembly control variable set meets the coupling evaluation threshold requirement, that is, the coupling evaluation coefficients of any two variables therein are less than the assembly control variable coupling evaluation threshold.

[0030] According to the shock absorber assembly control variable constraint matrix, component assembly control decisions are made on the H shock absorber components to obtain a shock absorber assembly control decision population.

[0031] In the process of shock absorber assembly, assembly control decisions are made for H shock absorber components according to the shock absorber assembly control variable constraint matrix, that is, a set of assembly control variable values ​​that meet the constraints is randomly generated for each shock absorber component, and multiple shock absorber assembly control decision seeds are generated to form a shock absorber assembly control decision population.

[0032] Construct the shock absorber assembly control fitness function and assembly control decision reproduction constraint function;

[0033] In the optimization process of shock absorber assembly control, the shock absorber assembly control optimization is carried out by constructing the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, wherein the shock absorber assembly control fitness function is used to evaluate the performance of each assembly control decision, and the assembly control decision reproduction constraint function is used to determine which decisions can participate in the next generation reproduction process of the evolutionary algorithm.

[0034] Furthermore, the shock absorber assembly control fitness function is:

[0035]

[0036] Among them, f represents the control adaptability of the shock absorber assembly, , Characterize the weight condition for calculating the fitness of the shock absorber assembly control, , are all positive numbers, , The sum of is 1, Characterizes the predicted assembly quality coefficient corresponding to the h-th shock absorber component, Characterizes the predicted assembly efficiency coefficient corresponding to the h-th shock absorber assembly, where h is a positive integer, h belongs to H, and H is the total number of shock absorber assemblies in the shock absorber assembly production task.

[0037] The shock absorber assembly control fitness function combines the predicted assembly quality coefficient and predicted assembly efficiency coefficient , and by weight , Adjustment is performed to evaluate the performance of the assembly control decision. In the shock absorber assembly control fitness function, f represents the shock absorber assembly control fitness, , Characterize the weight condition for calculating the fitness of the shock absorber assembly control, , are all positive numbers, , The sum of is 1, Characterizes the predicted assembly quality coefficient corresponding to the h-th shock absorber component, Characterizes the predicted assembly efficiency coefficient corresponding to the h-th shock absorber assembly, where h is a positive integer, h belongs to H, and H is the total number of shock absorber assemblies in the shock absorber assembly production task.

[0038] Furthermore, the assembly control decision reproduction constraint function is:

[0039]

[0040] in, Characterizes the number of decision seeds corresponding to the g-th shock absorber assembly control decision seed, g is a positive integer, Characterizing the shock absorber assembly control fitness corresponding to the g-th shock absorber assembly control decision seed, Characterizes the lower limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the number of decision seed reproduction, Characterizes the lower limit of the number of decision seed reproduction, It means round down.

[0041] Assembly control decision reproduction constraint function Describes the fitness of the seed according to the shock absorber assembly control decision To determine the corresponding number of decision seeds to be propagated, it ensures that decision seeds with higher fitness will have more opportunities to participate in the subsequent optimization process. In the assembly control decision propagation constraint function, Characterizes the number of decision seeds corresponding to the g-th shock absorber assembly control decision seed, g is a positive integer, Characterizing the shock absorber assembly control fitness corresponding to the g-th shock absorber assembly control decision seed, Characterizes the lower limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the number of decision seed reproduction, Characterizes the lower limit of the number of decision seed reproduction, It means round down.

[0042] According to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, the shock absorber assembly control decision population is subjected to decision seed reproduction search and optimization to obtain a shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraints;

[0043] In the process of optimizing the shock absorber assembly control decision, decision seed propagation search and optimization are carried out based on the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision propagation constraint function to find the best assembly control decision that meets the constraint conditions, and then obtain the shock absorber assembly control optimization result that meets the propagation search optimization constraints.

[0044] Furthermore, according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision propagation constraint function, the shock absorber assembly control decision population is subjected to decision seed propagation search and optimization to obtain a shock absorber assembly control optimization result that satisfies the propagation search and optimization constraints, including:

[0045] According to the shock absorber assembly control fitness function, the shock absorber assembly control decision population is subjected to fitness analysis to obtain a first shock absorber assembly control fitness distribution; according to the first shock absorber assembly control fitness distribution, the shock absorber assembly control decision population is subjected to assembly control fitness maximization screening to determine a first shock absorber assembly control optimization seed; according to the assembly control decision reproduction constraint function and the first shock absorber assembly control fitness distribution, the first decision seed reproduction quantity distribution corresponding to the shock absorber assembly control decision population is calculated; based on the first decision seed reproduction quantity distribution and the shock absorber assembly control variable constraint matrix, the shock absorber assembly control decision population is subjected to constrained reproduction to obtain a first shock absorber assembly control decision reproduction population; based on the first shock absorber assembly control decision reproduction population, the first shock absorber assembly control optimization seed is subjected to iterative reproduction search and optimization according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function to obtain the shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraints.

[0046] Preferably, data related to shock absorber assembly are obtained, including historical assembly data, experimental data, simulation data, etc., which contain various parameters in the assembly process (such as assembly force, assembly speed, assembly temperature, etc.) and corresponding assembly quality and assembly efficiency results. A neural network model is trained based on these assembly data. After the training is completed, the shock absorber assembly control decision population is input into the neural network model, that is, the relevant parameters in the assembly process (such as assembly force, assembly speed, assembly temperature, etc.) are used as input, and then the predicted assembly quality coefficient and the predicted assembly efficiency coefficient are output; the predicted assembly quality coefficient and the predicted assembly efficiency coefficient are input into the shock absorber assembly control fitness function to evaluate the fitness of each individual in the shock absorber assembly control decision population, calculate the fitness value of each individual, and record the fitness distribution of the entire population, that is, the first shock absorber assembly control fitness distribution; according to the first shock absorber assembly control fitness distribution, the shock absorber assembly control decision population is screened, and individuals with higher fitness values ​​are selected as the first shock absorber assembly control optimization seeds; according to the assembly control decision breeding constraint function and ... the individuals with higher fitness values ​​are selected as the first shock absorber assembly control optimization seeds; according to the assembly control decision breeding constraint function and the first shock absorber assembly control fitness distribution, the shock absorber assembly control decision population is screened, and the individuals with higher fitness values ​​are selected as the first shock absorber assembly control optimization seeds; according to the The fitness distribution is calculated, and the reproduction number corresponding to each optimal seed is calculated. The reproduction number depends on the fitness value of the individual and the parameters in the reproduction constraint function, and the reproduction number distribution of the first decision seed is obtained; based on the reproduction number distribution of the first decision seed and the shock absorber assembly control variable constraint matrix, the shock absorber assembly control decision population is reproduced, and new decision individuals are generated through operations such as crossover and mutation to ensure that the new individuals meet the constraints in the shock absorber assembly control variable constraint matrix, and the first shock absorber assembly control decision reproduction population is obtained, which will be used as the input for the next round of iteration; based on the first shock absorber assembly control decision reproduction population, the fitness analysis, screening, calculation of reproduction number and constraint reproduction steps are repeated. In each iteration, the optimal seeds are iteratively reproduced and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function; as the iteration proceeds, the individuals in the population will gradually approach the optimal solution until the termination condition (such as reaching the maximum number of iterations) is met; after the iteration is completed, the individual with the highest fitness value in the final population is selected as the shock absorber assembly control optimization result.

[0047] Further, based on the first shock absorber assembly control decision breeding population, the first shock absorber assembly control optimization seed is iteratively propagated and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding and search optimization constraints, including:

[0048] According to the shock absorber assembly control fitness function, the first shock absorber assembly control decision breeding population is subjected to fitness analysis to obtain the second shock absorber assembly control fitness distribution; according to the second shock absorber assembly control fitness distribution, the first shock absorber assembly control decision breeding population and the first shock absorber assembly control optimization seed are subjected to assembly control fitness maximization optimization to determine the second shock absorber assembly control optimization seed; according to the assembly control decision breeding constraint function and the second shock absorber assembly control fitness distribution, the second decision seed breeding population corresponding to the first shock absorber assembly control decision breeding population is calculated. Based on the second decision seed breeding number distribution and the shock absorber assembly control variable constraint matrix, the first shock absorber assembly control decision breeding population is constrained to obtain a second shock absorber assembly control decision breeding population; based on the second shock absorber assembly control decision breeding population, the second shock absorber assembly control optimization seed is iteratively propagated and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding search optimization constraints.

[0049] Preferably, the shock absorber assembly control fitness function is applied to each individual in the first shock absorber assembly control decision breeding population, and its fitness value is calculated to obtain the second shock absorber assembly control fitness distribution, which reflects the performance of each individual in the current population; based on the second shock absorber assembly control fitness distribution, individuals with higher fitness are screened out from the first shock absorber assembly control decision breeding population and the first shock absorber assembly control optimization seeds, and these individuals with higher fitness will be regarded as second shock absorber assembly control optimization seeds, which will serve as the starting point for the next round of iterative breeding; using the assembly control decision breeding constraint function and the second shock absorber assembly control fitness distribution, the corresponding breeding quantity for each second shock absorber assembly control optimization seed is calculated to obtain the second decision seed breeding quantity distribution corresponding to the first shock absorber assembly control decision breeding population; according to the second decision seed breeding quantity distribution and the shock absorber assembly control variable constraint matrix, The first shock absorber assembly control decision breeding population is reproduced. During the breeding process, new decision individuals are generated through operations such as crossover and mutation, and it is ensured that these individuals meet the constraints in the shock absorber assembly control variable constraint matrix to obtain the second shock absorber assembly control decision breeding population, which will be used as the input for the next round of iteration; based on the second shock absorber assembly control decision breeding population, the fitness analysis, optimization, calculation of breeding quantity and constraint breeding are repeated. In each iteration, the shock absorber assembly control variable constraint matrix, shock absorber assembly control fitness function and assembly control decision breeding constraint function are used to iteratively breed and search for the second shock absorber assembly control optimization seed; as the iteration proceeds, the individuals in the population will gradually approach the optimal solution until the termination condition is met (such as reaching the maximum number of iterations); after the iteration is completed, the individual with the highest fitness value in the final population is selected as the shock absorber assembly control optimization result.

[0050] The H shock absorber assemblies are assembled and controlled according to the shock absorber assembly control optimization result.

[0051] According to the optimization result of the shock absorber assembly control, the H shock absorber components are assembled and controlled, that is, they are assembled according to a predetermined assembly sequence and assembly parameters, so as to improve the assembly quality and efficiency.

[0052] In summary, the embodiments of the present application have at least the following technical effects:

[0053] First, a shock absorber assembly production task is received, wherein the shock absorber assembly production task includes H shock absorber components, wherein H is a positive integer greater than 1. Then, variable constraint modulation is performed on the H shock absorber components according to the assembly control variable optimization breadth constraint, and a shock absorber assembly control variable constraint matrix is ​​established. Then, component assembly control decisions are made on the H shock absorber components according to the shock absorber assembly control variable constraint matrix, and a shock absorber assembly control decision population is obtained. Next, a shock absorber assembly control fitness function and an assembly control decision reproduction constraint function are constructed. Further, a decision seed reproduction search is performed on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, and a shock absorber assembly control optimization result that satisfies the reproduction search optimization constraint is obtained. Finally, assembly control is performed on the H shock absorber components according to the shock absorber assembly control optimization result. The technical problem of low assembly efficiency in the shock absorber assembly production process in the prior art is solved, and the technical effect of improving assembly efficiency is achieved.

[0054] Embodiment 2

[0055] Based on the same inventive concept as the intelligent control method for shock absorber assembly production in the aforementioned embodiment, Figure 2 As shown, the present application provides an intelligent control device for shock absorber assembly production, and the device and method embodiments in the present application are based on the same inventive concept. The device includes:

[0056] A receiving module 11, wherein the receiving module 11 is used to receive a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber components, wherein H is a positive integer greater than 1; a variable constraint modulation module 12, wherein the variable constraint modulation module 12 is used to perform variable constraint modulation on the H shock absorber components according to the assembly control variable optimization breadth constraint, and establish a shock absorber assembly control variable constraint matrix; an assembly control decision module 13, wherein the assembly control decision module 13 is used to perform component assembly control decision on the H shock absorber components according to the shock absorber assembly control variable constraint matrix, and obtain a shock absorber assembly control decision population; A function construction module 14, the function construction module 14 is used to construct a shock absorber assembly control fitness function and an assembly control decision propagation constraint function; an optimization module 15, the optimization module 15 is used to perform decision seed propagation search and optimization on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision propagation constraint function, to obtain a shock absorber assembly control optimization result that satisfies the propagation search optimization constraints; an assembly control module 16, the assembly control module 16 is used to perform assembly control on the H shock absorber components according to the shock absorber assembly control optimization result.

[0057] Furthermore, the variable constraint modulation module 12 is used to perform the following method:

[0058] According to the H shock absorber components, assembly control variables are retrieved to obtain a first shock absorber component assembly control variable set; according to the first shock absorber component assembly control variable set, coupling reduction optimization is performed to obtain a second shock absorber component assembly control variable set; according to the second shock absorber component assembly control variable set, assembly control value evaluation is performed to obtain a variable assembly control value evaluation distribution; according to the variable assembly control value evaluation distribution, the second shock absorber component assembly control variable set is arranged in descending order to obtain a third shock absorber component assembly control variable set; according to the assembly control variable optimization breadth constraint, the third shock absorber component assembly control variable set is optimized and screened to obtain a fourth shock absorber component assembly control variable set, wherein the assembly control variable optimization breadth constraint includes a component assembly control variable optimization dimension threshold; based on the fourth shock absorber component assembly control variable set, variable constraint information of the H shock absorber components is collected to generate the shock absorber assembly control variable constraint matrix.

[0059] Furthermore, the variable constraint modulation module 12 is used to perform the following method:

[0060] According to the first shock absorber assembly control variable set, pairwise coupling evaluation is performed to obtain an assembly control variable coupling evaluation set; an assembly control variable coupling evaluation threshold is obtained; according to the assembly control variable coupling evaluation threshold and the assembly control variable coupling evaluation set, the first shock absorber assembly control variable set is subjected to coupling reduction optimization to obtain the second shock absorber assembly control variable set whose arbitrary assembly control variable coupling evaluation coefficient is less than the assembly control variable coupling evaluation threshold.

[0061] Furthermore, the function construction module 14 is used to execute the following method:

[0062] The shock absorber assembly control fitness function is:

[0063]

[0064] Among them, f represents the control adaptability of the shock absorber assembly, , Characterize the weight condition for calculating the fitness of the shock absorber assembly control, , are all positive numbers, , The sum of is 1, Characterizes the predicted assembly quality coefficient corresponding to the h-th shock absorber component, Characterizes the predicted assembly efficiency coefficient corresponding to the h-th shock absorber assembly, where h is a positive integer, h belongs to H, and H is the total number of shock absorber assemblies in the shock absorber assembly production task.

[0065] Furthermore, the function construction module 14 is used to execute the following method:

[0066] The assembly control decision reproduction constraint function is:

[0067]

[0068] in, Characterizes the number of decision seeds corresponding to the g-th shock absorber assembly control decision seed, g is a positive integer, Characterizing the shock absorber assembly control fitness corresponding to the g-th shock absorber assembly control decision seed, Characterizes the lower limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the number of decision seed reproduction, Characterizes the lower limit of the number of decision seed reproduction, It means round down.

[0069] Furthermore, the optimization module 15 is used to execute the following method:

[0070] According to the shock absorber assembly control fitness function, the shock absorber assembly control decision population is subjected to fitness analysis to obtain a first shock absorber assembly control fitness distribution; according to the first shock absorber assembly control fitness distribution, the shock absorber assembly control decision population is subjected to assembly control fitness maximization screening to determine a first shock absorber assembly control optimization seed; according to the assembly control decision reproduction constraint function and the first shock absorber assembly control fitness distribution, the first decision seed reproduction quantity distribution corresponding to the shock absorber assembly control decision population is calculated; based on the first decision seed reproduction quantity distribution and the shock absorber assembly control variable constraint matrix, the shock absorber assembly control decision population is subjected to constrained reproduction to obtain a first shock absorber assembly control decision reproduction population; based on the first shock absorber assembly control decision reproduction population, the first shock absorber assembly control optimization seed is subjected to iterative reproduction search and optimization according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function to obtain the shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraints.

[0071] Furthermore, the optimization module 15 is used to execute the following method:

[0072] According to the shock absorber assembly control fitness function, the first shock absorber assembly control decision breeding population is subjected to fitness analysis to obtain the second shock absorber assembly control fitness distribution; according to the second shock absorber assembly control fitness distribution, the first shock absorber assembly control decision breeding population and the first shock absorber assembly control optimization seed are subjected to assembly control fitness maximization optimization to determine the second shock absorber assembly control optimization seed; according to the assembly control decision breeding constraint function and the second shock absorber assembly control fitness distribution, the second decision seed breeding population corresponding to the first shock absorber assembly control decision breeding population is calculated. Based on the second decision seed breeding number distribution and the shock absorber assembly control variable constraint matrix, the first shock absorber assembly control decision breeding population is constrained to obtain a second shock absorber assembly control decision breeding population; based on the second shock absorber assembly control decision breeding population, the second shock absorber assembly control optimization seed is iteratively propagated and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding search optimization constraints.

[0073] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

[0075] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An intelligent control method for shock absorber assembly production, characterized in that: The method comprises: Receiving a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber assemblies, wherein H is a positive integer greater than 1; According to the assembly control variable optimization breadth constraint, the H shock absorber components are subjected to variable constraint modulation to establish a shock absorber assembly control variable constraint matrix; Performing assembly control decisions on the H shock absorber components according to the shock absorber assembly control variable constraint matrix to obtain a shock absorber assembly control decision population; Construct the shock absorber assembly control fitness function and assembly control decision reproduction constraint function; According to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, the shock absorber assembly control decision population is subjected to decision seed reproduction search and optimization to obtain a shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraints; Performing assembly control on the H shock absorber assemblies according to the shock absorber assembly control optimization result; According to the assembly control variable optimization breadth constraint, the H shock absorber components are subjected to variable constraint modulation, and a shock absorber assembly control variable constraint matrix is ​​established, including: Performing assembly control variable retrieval according to the H shock absorber assemblies to obtain a first shock absorber assembly control variable set; Performing decoupling optimization according to the first shock absorber assembly control variable set to obtain a second shock absorber assembly control variable set; Performing assembly control value evaluation according to the second shock absorber assembly control variable set to obtain variable assembly control value evaluation distribution; Arranging the second shock absorber assembly control variable set in descending order according to the variable assembly control value evaluation distribution to obtain a third shock absorber assembly control variable set; The third shock absorber assembly control variable set is optimized and screened according to the assembly control variable optimization breadth constraint to obtain a fourth shock absorber assembly control variable set, wherein the assembly control variable optimization breadth constraint includes a component assembly control variable optimization dimension threshold; Collecting variable constraint information of the H shock absorber assemblies based on the fourth shock absorber assembly control variable set to generate the shock absorber assembly control variable constraint matrix; According to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision reproduction constraint function, the shock absorber assembly control decision population is subjected to decision seed reproduction search and optimization to obtain a shock absorber assembly control optimization result that satisfies the reproduction search and optimization constraints, including: performing fitness analysis on the shock absorber assembly control decision population according to the shock absorber assembly control fitness function to obtain a first shock absorber assembly control fitness distribution; According to the first shock absorber assembly control fitness distribution, the shock absorber assembly control decision population is screened for assembly control fitness maximization to determine the first shock absorber assembly control optimization seed; Calculating the first decision seed reproduction quantity distribution corresponding to the shock absorber assembly control decision population according to the assembly control decision reproduction constraint function and the first shock absorber assembly control fitness distribution; Based on the first decision seed propagation quantity distribution and the shock absorber assembly control variable constraint matrix, constraining the shock absorber assembly control decision population to obtain a first shock absorber assembly control decision propagation population; Based on the first shock absorber assembly control decision breeding population, the first shock absorber assembly control optimization seed is iteratively bred and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding and search optimization constraints.

2. The intelligent control method for shock absorber assembly production according to claim 1, characterized in that: Performing coupling reduction optimization according to the first shock absorber assembly control variable set to obtain a second shock absorber assembly control variable set includes: Performing pairwise coupling evaluation according to the first shock absorber assembly control variable set to obtain an assembly control variable coupling evaluation set; Obtaining the assembly control variable coupling evaluation threshold; The first shock absorber assembly control variable set is subjected to coupling reduction optimization according to the assembly control variable coupling evaluation threshold and the assembly control variable coupling evaluation set to obtain the second shock absorber assembly control variable set whose arbitrary assembly control variable coupling evaluation coefficient is less than the assembly control variable coupling evaluation threshold.

3. The intelligent control method for shock absorber assembly production according to claim 1, characterized in that: The shock absorber assembly control fitness function is: Among them, f represents the control adaptability of the shock absorber assembly, , Characterize the weight condition for calculating the fitness of the shock absorber assembly control, , are all positive numbers, , The sum of is 1, Characterizes the predicted assembly quality coefficient corresponding to the h-th shock absorber component, Characterizes the predicted assembly efficiency coefficient corresponding to the h-th shock absorber assembly, where h is a positive integer, h belongs to H, and H is the total number of shock absorber assemblies in the shock absorber assembly production task.

4. The intelligent control method for shock absorber assembly production according to claim 1, characterized in that: The assembly control decision reproduction constraint function is: in, Characterizes the number of decision seeds corresponding to the g-th shock absorber assembly control decision seed, g is a positive integer, Characterizing the shock absorber assembly control fitness corresponding to the g-th shock absorber assembly control decision seed, Characterizes the lower limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the current shock absorber assembly control fitness, Characterizes the upper limit of the number of decision-making seed reproduction, Characterizes the lower limit of the number of decision seed reproduction, It means round down.

5. The intelligent control method for shock absorber assembly production according to claim 1, characterized in that: Based on the first shock absorber assembly control decision breeding population, the first shock absorber assembly control optimization seed is iteratively propagated and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding and search optimization constraint, including: Performing fitness analysis on the first shock absorber assembly control decision breeding population according to the shock absorber assembly control fitness function to obtain a second shock absorber assembly control fitness distribution; According to the second shock absorber assembly control fitness distribution, the first shock absorber assembly control decision breeding population and the first shock absorber assembly control optimization seed are optimized by maximizing the assembly control fitness to determine the second shock absorber assembly control optimization seed; Calculating the second decision seed reproduction quantity distribution corresponding to the first shock absorber assembly control decision reproduction population according to the assembly control decision reproduction constraint function and the second shock absorber assembly control fitness distribution; Based on the second decision seed propagation quantity distribution and the shock absorber assembly control variable constraint matrix, constraining the propagation of the first shock absorber assembly control decision propagation population to obtain a second shock absorber assembly control decision propagation population; Based on the second shock absorber assembly control decision breeding population, the second shock absorber assembly control optimization seed is iteratively bred and searched according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision breeding constraint function to obtain the shock absorber assembly control optimization result that satisfies the breeding search optimization constraints.

6. An intelligent control device for shock absorber assembly production, characterized in that: The device is used to implement the intelligent control method for shock absorber assembly production according to any one of claims 1 to 5, comprising: A receiving module, the receiving module is used to receive a shock absorber assembly production task, wherein the shock absorber assembly production task includes H shock absorber assemblies, wherein H is a positive integer greater than 1; A variable constraint modulation module, the variable constraint modulation module is used to perform variable constraint modulation on the H shock absorber components according to the assembly control variable optimization breadth constraint, and establish a shock absorber assembly control variable constraint matrix; An assembly control decision module, wherein the assembly control decision module is used to perform assembly control decisions on the H shock absorber components according to the shock absorber assembly control variable constraint matrix to obtain a shock absorber assembly control decision population; A function building module, wherein the function building module is used to build a shock absorber assembly control fitness function and an assembly control decision reproduction constraint function; An optimization module, wherein the optimization module is used to perform decision seed propagation search and optimization on the shock absorber assembly control decision population according to the shock absorber assembly control variable constraint matrix, the shock absorber assembly control fitness function and the assembly control decision propagation constraint function, to obtain a shock absorber assembly control optimization result that satisfies the propagation search and optimization constraints; An assembly control module is used to perform assembly control on the H shock absorber assemblies according to the shock absorber assembly control optimization result.

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